Possible nutrient data infill from EGRET package
https://github.com/DOI-USGS/EGRET/blob/main/R/readUserDaily.r
https://cran.r-project.org/web/packages/EGRET/vignettes/EGRET.html
library(EGRET)
egret_BWL_N <- read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_BWL_NO31.csv") %>%
mutate(NO3_mgL_dl = if_else(ConcAve < 0.0015, 0.0015, ConcAve))%>%
mutate(NO3_mgL_m = if_else(ConcDay_mod < 0.0015, 0.0015, ConcDay_mod))%>%
mutate(NO3_mgL_i = if_else(is.na(NO3_mgL_dl), NO3_mgL_m, NO3_mgL_dl))%>%
mutate(date = as.Date(Date)) %>%
mutate(site="BWL") %>%
dplyr::select(date, site, NO3_mgL_i, NO3_mgL_dl, NO3_mgL_m) %>%
dplyr::group_by(date, site) %>%
summarise(across(everything(), mean, na.rm = TRUE), .groups = "drop")
infill_count <- sum(is.na(read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_BWL_NO31.csv")$ConcAve))
infill_count
## [1] 0
# Create the plot
logQ_plt <- ggplot(egret_BWL_N, aes(x = date)) +
# Sample data as black points
geom_point(aes(y = NO3_mgL_dl, color = "Sampled N"), alpha = 0.9) +
geom_line(aes(y = NO3_mgL_dl, color = "Sampled N")) +
# Modeled data as red triangles
geom_point(aes(y = NO3_mgL_m, color = "Modeled N"), shape = 2, alpha = 0.9) +
geom_line(aes(y = NO3_mgL_m, color = "Modeled N"), alpha = 0.9) +
scale_color_manual(values = c("Sampled N" = "black", "Modeled N" = "#D62828")) +
scale_x_date(date_breaks = "4 months", date_labels = "%b %Y") + # Set breaks every 4 months
theme_bw() + labs(title = "BWL NO3") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
logQ_plt

egret_BWL_A <- read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_BWL_NH4.csv") %>%
mutate(NH4_mgL_dl = if_else(ConcAve < 0.0015, 0.0015, ConcAve))%>%
mutate(NH4_mgL_m = if_else(ConcDay_mod < 0.0015, 0.0015, ConcDay_mod))%>%
mutate(NH4_mgL_i = if_else(is.na(NH4_mgL_m), NH4_mgL_m, NH4_mgL_m))%>%
mutate(date = as.Date(Date)) %>%
mutate(site="BWL") %>%
dplyr::select(date, site, NH4_mgL_i, NH4_mgL_dl, NH4_mgL_m) %>%
dplyr::group_by(date, site) %>%
summarise(across(everything(), mean, na.rm = TRUE), .groups = "drop")
infill_count <- sum(is.na(read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_BWL_NH4.csv")$ConcAve))
infill_count
## [1] 22
# Create the plot
logQ_plt1 <- ggplot(egret_BWL_A, aes(x = date)) +
# Sample data as black points
geom_point(aes(y = NH4_mgL_dl, color = "Sampled N"), alpha = 0.9) +
geom_line(aes(y = NH4_mgL_dl, color = "Sampled N")) +
# Modeled data as red triangles
geom_point(aes(y = NH4_mgL_m, color = "Modeled N"), shape = 2, alpha = 0.9) +
geom_line(aes(y = NH4_mgL_m, color = "Modeled N"), alpha = 0.9) +
scale_color_manual(values = c("Sampled N" = "black", "Modeled N" = "#D62828")) +
scale_x_date(date_breaks = "4 months", date_labels = "%b %Y") + # Set breaks every 4 months
theme_bw() + labs(title = "BWL NH4") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
logQ_plt1

###
egret_BWU_N <- read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_BWU_NO3.csv") %>%
mutate(NO3_mgL_dl = if_else(ConcAve < 0.0015, 0.0015, ConcAve))%>%
mutate(NO3_mgL_m = if_else(ConcDay_mod < 0.0015, 0.0015, ConcDay_mod))%>%
mutate(NO3_mgL_i = if_else(is.na(NO3_mgL_dl), NO3_mgL_m, NO3_mgL_dl))%>%
mutate(date = as.Date(Date)) %>%
mutate(site="BWU") %>%
dplyr::select(date, site, NO3_mgL_i, NO3_mgL_dl, NO3_mgL_m) %>%
dplyr::group_by(date, site) %>%
summarise(across(everything(), mean, na.rm = TRUE), .groups = "drop")
infill_count <- sum(is.na(read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_BWU_NO3.csv")$ConcAve))
infill_count
## [1] 4
# Create the plot
logQ_plt2 <- ggplot(egret_BWU_N, aes(x = date)) +
# Sample data as black points
geom_point(aes(y = NO3_mgL_dl, color = "Sampled N"), alpha = 0.9) +
geom_line(aes(y = NO3_mgL_dl, color = "Sampled N")) +
# Modeled data as red triangles
geom_point(aes(y = NO3_mgL_m, color = "Modeled N"), shape = 2, alpha = 0.9) +
geom_line(aes(y = NO3_mgL_m, color = "Modeled N"), alpha = 0.9) +
scale_color_manual(values = c("Sampled N" = "black", "Modeled N" = "#D62828")) +
scale_x_date(date_breaks = "4 months", date_labels = "%b %Y") + # Set breaks every 4 months
theme_bw() + labs(title = "BWU NO3") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
logQ_plt2

egret_BWU_A <- read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_BWU_NH4.csv") %>%
mutate(NH4_mgL_dl = if_else(ConcAve < 0.0015, 0.0015, ConcAve))%>%
mutate(NH4_mgL_m = if_else(ConcDay_mod < 0.0015, 0.0015, ConcDay_mod))%>%
mutate(NH4_mgL_i = if_else(is.na(NH4_mgL_m), NH4_mgL_m, NH4_mgL_m))%>%
mutate(date = as.Date(Date)) %>%
mutate(site="BWU") %>%
dplyr::select(date, site, NH4_mgL_i, NH4_mgL_dl, NH4_mgL_m) %>%
dplyr::group_by(date, site) %>%
summarise(across(everything(), mean, na.rm = TRUE), .groups = "drop")
infill_count <- sum(is.na(read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_BWU_NH4.csv")$ConcAve))
infill_count
## [1] 5
# Create the plot
logQ_plt3 <- ggplot(egret_BWU_A, aes(x = date)) +
# Sample data as black points
geom_point(aes(y = NH4_mgL_dl, color = "Sampled N"), alpha = 0.9) +
geom_line(aes(y = NH4_mgL_dl, color = "Sampled N")) +
# Modeled data as red triangles
geom_point(aes(y = NH4_mgL_m, color = "Modeled N"), shape = 2, alpha = 0.9) +
geom_line(aes(y = NH4_mgL_m, color = "Modeled N"), alpha = 0.9) +
scale_color_manual(values = c("Sampled N" = "black", "Modeled N" = "#D62828")) +
scale_x_date(date_breaks = "4 months", date_labels = "%b %Y") + # Set breaks every 4 months
theme_bw() + labs(title = "BWU NH4") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
logQ_plt3

###
egret_GBL_N <- read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_GBL_NO3.csv") %>%
mutate(NO3_mgL_dl = if_else(ConcAve < 0.0015, 0.0015, ConcAve))%>%
mutate(NO3_mgL_m = if_else(ConcDay_mod < 0.0015, 0.0015, ConcDay_mod))%>%
mutate(NO3_mgL_i = if_else(is.na(NO3_mgL_dl), NO3_mgL_m, NO3_mgL_dl))%>%
mutate(date = as.Date(Date)) %>%
mutate(site="GBL") %>%
dplyr::select(date, site, NO3_mgL_i, NO3_mgL_dl, NO3_mgL_m) %>%
dplyr::group_by(date, site) %>%
summarise(across(everything(), mean, na.rm = TRUE), .groups = "drop")
infill_count <- sum(is.na(read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_GBL_NO3.csv")$ConcAve))
infill_count
## [1] 8
# Create the plot
logQ_plt4 <- ggplot(egret_GBL_N, aes(x = date)) +
# Sample data as black points
geom_point(aes(y = NO3_mgL_dl, color = "Sampled N"), alpha = 0.9) +
geom_line(aes(y = NO3_mgL_dl, color = "Sampled N")) +
# Modeled data as red triangles
geom_point(aes(y = NO3_mgL_m, color = "Modeled N"), shape = 2, alpha = 0.9) +
geom_line(aes(y = NO3_mgL_m, color = "Modeled N"), alpha = 0.9) +
scale_color_manual(values = c("Sampled N" = "black", "Modeled N" = "#D62828")) +
scale_x_date(date_breaks = "4 months", date_labels = "%b %Y") + # Set breaks every 4 months
theme_bw() + labs(title = "GBL NO3") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
logQ_plt4

egret_GBL_A <- read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_GBL_NH4.csv") %>%
mutate(NH4_mgL_dl = if_else(ConcAve < 0.0015, 0.0015, ConcAve))%>%
mutate(NH4_mgL_m = if_else(ConcDay_mod < 0.0015, 0.0015, ConcDay_mod))%>%
mutate(NH4_mgL_i = if_else(is.na(NH4_mgL_m), NH4_mgL_m, NH4_mgL_m))%>%
mutate(date = as.Date(Date)) %>%
mutate(site="GBL") %>%
dplyr::select(date, site, NH4_mgL_i, NH4_mgL_dl, NH4_mgL_m) %>%
dplyr::group_by(date, site) %>%
summarise(across(everything(), mean, na.rm = TRUE), .groups = "drop")
infill_count <- sum(is.na(read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_GBL_NH4.csv")$ConcAve))
infill_count
## [1] 10
# Create the plot
logQ_plt5 <- ggplot(egret_GBL_A, aes(x = date)) +
# Sample data as black points
geom_point(aes(y = NH4_mgL_dl, color = "Sampled N"), alpha = 0.9) +
geom_line(aes(y = NH4_mgL_dl, color = "Sampled N")) +
# Modeled data as red triangles
geom_point(aes(y = NH4_mgL_m, color = "Modeled N"), shape = 2, alpha = 0.9) +
geom_line(aes(y = NH4_mgL_m, color = "Modeled N"), alpha = 0.9) +
scale_color_manual(values = c("Sampled N" = "black", "Modeled N" = "#D62828")) +
scale_x_date(date_breaks = "4 months", date_labels = "%b %Y") + # Set breaks every 4 months
theme_bw() + labs(title = "GBL NH4") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
logQ_plt5

###
egret_GBU_N <- read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_GBU_NO3.csv") %>%
mutate(NO3_mgL_dl = if_else(ConcAve < 0.0015, 0.0015, ConcAve))%>%
mutate(NO3_mgL_m = if_else(ConcDay_mod < 0.0015, 0.0015, ConcDay_mod))%>%
mutate(NO3_mgL_i = if_else(is.na(NO3_mgL_dl), NO3_mgL_m, NO3_mgL_dl))%>%
mutate(date = as.Date(Date)) %>%
mutate(site="GBU") %>%
dplyr::select(date, site, NO3_mgL_i, NO3_mgL_dl, NO3_mgL_m) %>%
dplyr::group_by(date, site) %>%
summarise(across(everything(), mean, na.rm = TRUE), .groups = "drop")
infill_count <- sum(is.na(read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_GBU_NO3.csv")$ConcAve))
infill_count
## [1] 11
# Create the plot
logQ_plt6 <- ggplot(egret_GBU_N, aes(x = date)) +
# Sample data as black points
geom_point(aes(y = NO3_mgL_dl, color = "Sampled N"), alpha = 0.9) +
geom_line(aes(y = NO3_mgL_dl, color = "Sampled N")) +
# Modeled data as red triangles
geom_point(aes(y = NO3_mgL_m, color = "Modeled N"), shape = 2, alpha = 0.9) +
geom_line(aes(y = NO3_mgL_m, color = "Modeled N"), alpha = 0.9) +
scale_color_manual(values = c("Sampled N" = "black", "Modeled N" = "#D62828")) +
scale_x_date(date_breaks = "4 months", date_labels = "%b %Y") + # Set breaks every 4 months
theme_bw() + labs(title = "GBU NO3") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
logQ_plt6

egret_GBU_A <- read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_GBU_NH4.csv") %>%
mutate(NH4_mgL_dl = if_else(ConcAve < 0.0015, 0.0015, ConcAve))%>%
mutate(NH4_mgL_m = if_else(ConcDay_mod < 0.0015, 0.0015, ConcDay_mod))%>%
mutate(NH4_mgL_i = if_else(is.na(NH4_mgL_m), NH4_mgL_m, NH4_mgL_m))%>%
mutate(date = as.Date(Date)) %>%
mutate(site="GBU") %>%
dplyr::select(date, site, NH4_mgL_i, NH4_mgL_dl, NH4_mgL_m) %>%
dplyr::group_by(date, site) %>%
summarise(across(everything(), mean, na.rm = TRUE), .groups = "drop")
infill_count <- sum(is.na(read.csv("/Users/kellyloria/Documents/Publications/CH1\ biogeochem\ linkages/EGRET_GBU_NH4.csv")$ConcAve))
infill_count
## [1] 12
# Create the plot
logQ_plt7 <- ggplot(egret_GBU_A, aes(x = date)) +
# Sample data as black points
geom_point(aes(y = NH4_mgL_dl, color = "Sampled N"), alpha = 0.9) +
geom_line(aes(y = NH4_mgL_dl, color = "Sampled N")) +
# Modeled data as red triangles
geom_point(aes(y = NH4_mgL_m, color = "Modeled N"), shape = 2, alpha = 0.9) +
geom_line(aes(y = NH4_mgL_m, color = "Modeled N"), alpha = 0.9) +
scale_color_manual(values = c("Sampled N" = "black", "Modeled N" = "#D62828")) +
scale_x_date(date_breaks = "4 months", date_labels = "%b %Y") + # Set breaks every 4 months
theme_bw() + labs(title = "GBL NH4") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
logQ_plt7

nitrogen_dat <- rbind(egret_BWL_N,
egret_BWU_N,
egret_GBL_N,
egret_GBU_N)
nitrogen_datA <- rbind(egret_BWL_A,
egret_BWU_A,
egret_GBL_A,
egret_GBU_A)
nitrogen_data <- nitrogen_dat %>% full_join(nitrogen_datA, by=c("date", "site"))